PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Large-Scale Multiclass Transduction
Thomas Geartner, quoc le, Simon Burton, Alex Smola and S V N Vishwanathan
Advances in Neural Information Processing Systems Volume 18, 2005.

Abstract

We present a method for performing transductive inference on very large datasets. Our algorithm is based on multiclass Gaussian processes and is effective whenever the multiplication of the kernel matrix or its inverse with a vector can be performed sufficiently fast. This holds, for instance, for certain graph and string kernels. Transduction is achieved by variational inference over the unlabeled data subject to a balancing constraint.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:2014
Deposited By:quoc le
Deposited On:15 January 2006